The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In face recognition, traditional linear dimensionality reduction methods can not be good at keeping the intrinsic distribution of face sample data. While Locally Linear Embedding (LLE) algorithm, which belongs to manifold learning, has the advantage of keeping the intrinsic distribution of face sample data. Principal Component Analysis (PCA) possesses the merits of high recognition efficiency. An...
Recently, locality sensitive discriminant analysis (LSDA) was proposed for dimensionality reduction. As far as matrix data, such as images, they are often vectorized for LSDA algorithm to find the intrinsic manifold structure. Such a matrix-to-vector transform may cause the loss of some structural information residing in original 2D images. Firstly, this paper proposes an algorithm named two-dimensional...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.